There is a field of detection devices and systems designed to detect for the presence of substances harmful to humans, such as those used in chemical or biological warfare. During the design stage and prior to deployment, it is desirable to test and evaluate the performance of such detection systems. Since high-fidelity performance evaluation of active and passive remote sensors requires significant amounts of empirical data, one option is to test the detection systems in a real-world situation where a harmful substance is disseminated and the detection system is used to detect the substance.
Surface contamination can be the result of an accident or intentional dispersal of the contaminant, and therefore the surface contamination can consist of a single substance or multiple substances in bulk form or distributed over an area. Examples of persistent patches of contamination are bulk material, thin layers, small droplets or small particles.
Spectroscopy techniques are used to analyze substances and techniques have been developed for the non-destructive testing of surface-deposited substances in solid and liquid phases. Such techniques include Fourier Transform Infrared Spectroscopy (FTIR), X-ray fluorescence, gas chromatography and mass spectrometry (GC-MS), and Raman spectroscopy. Traditional surface hazard detectors include “point-and-shoot” devices, in which the device operator holds a sensing probe on a specific location. The performance of these kinds of detectors can be easily tested in the laboratory by exposing the sensor to variable doses of substances in a static mode. A new breed of surface contamination sensors based on the Laser Interrogation of Surface Agents (LISA) technique (as disclosed in U.S. Pat. No. 6,788,407 B1) affords new concepts of operation since these LISA sensors can probe the surface contaminants in near real time (˜40 ms). This added capability translates into new ways of searching a potentially contaminated scene: systematic scan, random and adaptive scan strategies can be used to detect trace contaminants invisible to the naked eye. The performance of such devices will depend on a rich set of parameters such as, but not limited to, scan speed, scan patterns, contaminant distribution pattern and contamination type. Testing the effectiveness of such sensors in a realistic scene is costly, time-intensive and potentially dangerous.
Evaluation of a detection system can be more effectively performed using a computer model that accurately describes a user-selectable contamination scene and the interaction of a specific sensor configuration with that scene. Starting with a given contamination scene (i.e. substance types, size-distribution profiles, contamination densities, dispersal patches sizes and locations), performance metrics such as probability of detection and time-to-detect values can be quickly evaluated for a number of sensor configurations and operational scenarios. No other known model simultaneously tracks both substance dispersal positions and quantities along with substance properties and sensor interrogation and detection capabilities.